New predictive analytics model identifies congestive heart failure patients with high readmission risk

Readmission of patients with chronic diseases is a growing problem, costing the U.S. health care system about $25 billion each year. Researchers at The University of Texas at Dallas developed a predictive analytics model that can identify congestive heart failure patients with high readmission risk and potentially help stymie those costs.

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